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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSun, 14 Dec 2008 13:29:09 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/14/t1229286591qakhufsrmmx6qm5.htm/, Retrieved Wed, 15 May 2024 06:08:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33559, Retrieved Wed, 15 May 2024 06:08:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsgdm
Estimated Impact151

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Werkloosheid bij 50+] [2008-12-14 20:29:09] [99f79d508deef838ee89a56fb32f134e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
88900
87280
85519
83647
81616
80100
94027
102327
104296
101593
94816
93535
93618
92330
90751
88576
86102
85494
103432
108870
109713
106960
103195
102348
102158
100431
97649
95611
93035
93579
111777
116065
116609
112934
107660
107965
107772
106201
102288
99217
96511
96456
113021
117836
118492
113922
109317
107496
105524
103824
101833
99436
96915
96072
111941
116008
117557
113445
108762
106661
102824
101912
99005
97894
96256
95606
108948
111223
113142
106078
100992
97413

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33559&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33559&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33559&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
191471.33333333338279.2564920170324196
297615.759045.0080971369424219
3104622.758660.1591327495523574
4107377.4166666677644.1548966078222036
5106498.1666666677236.5818756111821485
6102607.755970.6079045604717536

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 91471.3333333333 & 8279.25649201703 & 24196 \tabularnewline
2 & 97615.75 & 9045.00809713694 & 24219 \tabularnewline
3 & 104622.75 & 8660.15913274955 & 23574 \tabularnewline
4 & 107377.416666667 & 7644.15489660782 & 22036 \tabularnewline
5 & 106498.166666667 & 7236.58187561118 & 21485 \tabularnewline
6 & 102607.75 & 5970.60790456047 & 17536 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33559&T=1

[TABLE]
[ROW][C]Standard Deviation-Mean Plot[/C][/ROW]
[ROW][C]Section[/C][C]Mean[/C][C]Standard Deviation[/C][C]Range[/C][/ROW]
[ROW][C]1[/C][C]91471.3333333333[/C][C]8279.25649201703[/C][C]24196[/C][/ROW]
[ROW][C]2[/C][C]97615.75[/C][C]9045.00809713694[/C][C]24219[/C][/ROW]
[ROW][C]3[/C][C]104622.75[/C][C]8660.15913274955[/C][C]23574[/C][/ROW]
[ROW][C]4[/C][C]107377.416666667[/C][C]7644.15489660782[/C][C]22036[/C][/ROW]
[ROW][C]5[/C][C]106498.166666667[/C][C]7236.58187561118[/C][C]21485[/C][/ROW]
[ROW][C]6[/C][C]102607.75[/C][C]5970.60790456047[/C][C]17536[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33559&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33559&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
191471.33333333338279.2564920170324196
297615.759045.0080971369424219
3104622.758660.1591327495523574
4107377.4166666677644.1548966078222036
5106498.1666666677236.5818756111821485
6102607.755970.6079045604717536






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha14764.5104949861
beta-0.068423077890745
S.D.0.084714719186745
T-STAT-0.807688186275084
p-value0.464561630944268

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 14764.5104949861 \tabularnewline
beta & -0.068423077890745 \tabularnewline
S.D. & 0.084714719186745 \tabularnewline
T-STAT & -0.807688186275084 \tabularnewline
p-value & 0.464561630944268 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33559&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]14764.5104949861[/C][/ROW]
[ROW][C]beta[/C][C]-0.068423077890745[/C][/ROW]
[ROW][C]S.D.[/C][C]0.084714719186745[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.807688186275084[/C][/ROW]
[ROW][C]p-value[/C][C]0.464561630944268[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33559&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33559&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha14764.5104949861
beta-0.068423077890745
S.D.0.084714719186745
T-STAT-0.807688186275084
p-value0.464561630944268






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha18.9981233487446
beta-0.87130458218627
S.D.1.14647361656643
T-STAT-0.759986596809558
p-value0.489591161832883
Lambda1.87130458218627

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 18.9981233487446 \tabularnewline
beta & -0.87130458218627 \tabularnewline
S.D. & 1.14647361656643 \tabularnewline
T-STAT & -0.759986596809558 \tabularnewline
p-value & 0.489591161832883 \tabularnewline
Lambda & 1.87130458218627 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33559&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]18.9981233487446[/C][/ROW]
[ROW][C]beta[/C][C]-0.87130458218627[/C][/ROW]
[ROW][C]S.D.[/C][C]1.14647361656643[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.759986596809558[/C][/ROW]
[ROW][C]p-value[/C][C]0.489591161832883[/C][/ROW]
[ROW][C]Lambda[/C][C]1.87130458218627[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33559&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33559&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha18.9981233487446
beta-0.87130458218627
S.D.1.14647361656643
T-STAT-0.759986596809558
p-value0.489591161832883
Lambda1.87130458218627


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
(n <- length(x))
(np <- floor(n / par1))
arr <- array(NA,dim=c(par1,np))
j <- 0
k <- 1
for (i in 1:(np*par1))
{
j = j + 1
arr[j,k] <- x[i]
if (j == par1) {
j = 0
k=k+1
}
}
arr
arr.mean <- array(NA,dim=np)
arr.sd <- array(NA,dim=np)
arr.range <- array(NA,dim=np)
for (j in 1:np)
{
arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
}
arr.mean
arr.sd
arr.range
(lm1 <- lm(arr.sd~arr.mean))
(lnlm1 <- lm(log(arr.sd)~log(arr.mean)))
(lm2 <- lm(arr.range~arr.mean))
bitmap(file='test1.png')
plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
dev.off()
bitmap(file='test2.png')
plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Section',header=TRUE)
a<-table.element(a,'Mean',header=TRUE)
a<-table.element(a,'Standard Deviation',header=TRUE)
a<-table.element(a,'Range',header=TRUE)
a<-table.row.end(a)
for (j in 1:np) {
a<-table.row.start(a)
a<-table.element(a,j,header=TRUE)
a<-table.element(a,arr.mean[j])
a<-table.element(a,arr.sd[j] )
a<-table.element(a,arr.range[j] )
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Lambda',header=TRUE)
a<-table.element(a,1-lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')